{"id":"W2808288731","doi":"10.1007/s12079-018-0469-z","title":"Modelling glioma invasion using 3D bioprinting and scaffold-free 3D culture","year":2018,"lang":"en","type":"article","venue":"Journal of Cell Communication and Signaling","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canada Research Chairs; Canadian Cancer Society; Faculty of Medicine, University of British Columbia","keywords":"3D cell culture; Glioma; Scaffold; Organoid; Parenchyma; Spheroid; 3D bioprinting; Progenitor cell; Cell culture; Neural stem cell; Pathology; Human brain; Cancer cell; Biology; Neuroscience; Cancer research; Stem cell; Medicine; Cancer; Biomedical engineering; Cell biology; Tissue engineering; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001335079,0.0001121964,0.0001836508,0.0002083427,0.0002560379,0.0001388614,0.0004069194,0.0001097722,0.00003450246],"category_scores_gemma":[0.0001260506,0.00009882868,0.00003714356,0.0002158314,0.0001496256,0.0002239588,0.0002727649,0.0004271903,0.000001973231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004194574,"about_ca_system_score_gemma":0.00002456196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001449348,"about_ca_topic_score_gemma":0.000001227121,"domain_scores_codex":[0.9988863,0.00009781487,0.0004353817,0.00008974852,0.0003038928,0.0001868611],"domain_scores_gemma":[0.998936,0.0001852654,0.000162847,0.0003109877,0.0002616421,0.0001432575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002982941,0.00003431441,0.0003974877,0.0002124361,0.00005034703,0.00000760506,0.002647137,0.03164519,0.9554279,0.0001410597,0.0001136412,0.009293086],"study_design_scores_gemma":[0.0005082125,0.00005686406,0.00002511179,0.0004867485,0.00002511853,0.0000872909,0.0003485364,0.9006487,0.09547282,0.0008825824,0.001319509,0.0001385034],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9268514,0.003950691,0.0674836,0.00005968999,0.00006740191,0.00005425106,5.180182e-7,0.00003001208,0.001502429],"genre_scores_gemma":[0.845766,0.001285461,0.1527793,0.00001811321,0.0001200716,3.563536e-7,6.378751e-7,0.00001794112,0.00001212757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8690035,"threshold_uncertainty_score":0.4030117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04110836650758579,"score_gpt":0.2798493221039228,"score_spread":0.238740955596337,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}